AB0167 SINGLE-CELL SPATIAL TRANSCRIPTOME ANALYSIS IDENTIFIES DISEASE-SPECIFIC FIBROBLASTS IN RHEUMATOID VASCULITIS
Authors: A. Tsujii, Y. Hoshida, T. Tamada, D. Kim, K. Yamamoto, A. Nakabayashi, M. Yoshimura, K. Isoda, S. Ohshima
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> Spatial transcriptome analysis is an advanced technique that adds spatial information to gene expression analyses to identify differences in gene expression based on the location in specimen tissues. It can also provide disease-specific gene expression data in individual cells. This method has the potential to identify important gene expression related to disease pathogenesis, which cannot be obtained through conventional bulk analysis. CosMx™ Spatial Molecular Imaging (SMI) is a platform for spatial transcriptome analysis of formalin-fixed paraffin-embedded tissue samples at subcellular resolution (NanoString® Technologies, Seattle, WA, USA). The use of high-plex in situ hybridization followed by cyclic hybridization of immunofluorescent detection reagents and imaging enables the localization and identification of approximately 1,000 RNA targets in situ, and antibody-based, machine learning-augmented cell segmentation with nuclear and membrane markers localizes these targets to individual cells[1]. Cutaneous vasculitis is characterized by vasculitis of small-sized vessels of the skin and causes skin lesions, such as purpura or ulcers, resulting in a low quality of life. A variety of autoimmune diseases can cause cutaneous vasculitis, but its pathogenesis is unknown. In particular, cutaneous vasculitis associated with rheumatoid arthritis (RA) (referred to as rheumatoid vasculitis) is often difficult to treat and is associated with high rates of premature mortality<sup>[2]</sup>. Histologically, cutaneous vasculitis associated with autoimmune diseases is characterized by fibrinoid degeneration or neutrophilic vasculitis; however, these findings are nonspecific and do not lead to a precise diagnosis. <h3>Objectives</h3> In the present study, we aimed to identify disease-specific cell types and gene expression via single-cell spatial transcriptome analysis of skin tissues from patients with autoimmune disease-associated cutaneous vasculitis. This can lead to improved diagnosis, pathogenesis understanding, and treatment. <h3>Methods</h3> Single-cell spatial transcriptome analysis was performed using NanoString's CosMx™ SMI on tissues from vasculitis associated with five autoimmune diseases, including rheumatoid vasculitis, and a case with toxic rashes as controls. Following data collection, NanoString's data processing pipeline¹ was used to identify transcripts, define cell locations and boundaries, and count the number of transcripts per cell to determine the expression profiles for each cell. Cell types were inferred from these expression data using InSituType<sup>[3]</sup> and a reference Human Cell Atlas skin dataset. Immunostaining was performed to validate the identified gene markers. <h3>Results</h3> A total of 35,503 cells and 4,530,981 transcripts were analyzed. Clustering of cells based on gene expression levels revealed cells with a high expression of several specific genes, including MMP1, in rheumatoid vasculitis. CosMx™ SMI analysis revealed that these cells were primarily located in the perivascular area (Figure 1A). Immunostaining with anti-MMP1 antibody (1:100; ab52631, Abcam) revealed that the cells were histologically fibroblasts (Figure 1B). These findings revealed that fibroblasts expressing MMP1 are specific to rheumatoid vasculitis. MMP1 is highly expressed in synovial fibroblasts in RA and plays a substantial role in disease pathogenesis<sup>[4]</sup>. Our results suggest that disease-specific fibroblasts expressing MMP-1 are involved in the pathogenesis of rheumatoid vasculitis. The pathological roles of MMP1 and other markers merit further investigation. <h3>Conclusion</h3> Single-cell spatial transcriptome analysis revealed fibroblasts specific to rheumatoid vasculitis. The result of this study might contribute to understanding of etiology and treatment of rheumatoid vasculitis. <h3>References</h3> [1] He S, et al. Nat Biotechnol. 2022;40:1794-1806, [2] Turesson C, et al. Curr Opin Rheumatol. 2009;21:35-40, [3] Danaher P, et al. bioRxiv. 202210.19.512902, [4] Vincenti MP, et al. Arthritis Res. 2002;4:157-64. <h3>Acknowledgements</h3> We would like to express my special thanks of gratitude to NanoString® Technologies for spatial transcriptome analysis. We would also like to thank Editage (www.editage.com) for English language editing. <h3>Disclosure of Interests</h3> None Declared.